Senior AI/ML Imaging Engineer - Computational Photography

sonyglobal; United States; Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Benefits eligible

Hybrid work model

Job summary

Sony Corporation of America is seeking a Senior Research Engineer for its US R&D Laboratory to research and develop AI/ML-based image processing, computational photography, and CV algorithms for next-gen imaging products.

The role is hybrid (3 days on-site) in San Jose, CA or Culver City, CA or fully remote after training, with occasional travel to Japan. Strong research background and publication history preferred.

Qualifications

• PhD in CS, EE, CE, math, or related field; exceptional MS candidates with 3+ years of experience may be considered.
• Experience in developing deep learning, ML, and/or AI algorithms from the ground up.
• Strong fundamentals in image/video processing, CV, or related areas a plus.
• Demonstrated research skills with publications and ability to evaluate recent work.
• Proficiency in Python and PyTorch; familiarity with C/C++ and Linux.

Responsibilities

• Research, design, and develop AI/ML methods for image processing and computer vision for Sony imaging products.
• Prototype ideas quickly and assess potential for commercialization.
• Collaborate with cross-functional teams across the US and Japan.
• Prepare technical documentation and potential journal articles.

Skills

Python

PyTorch

C/C++

Linux

Deep learning

Machine learning

Image processing

Computer vision

Research

Experiment design

Education

PhD in Computer Science or related field

MS + 3+ years experience

Tools

Python

PyTorch

C/C++

Linux

Job description

Sony Corporation of America is seeking a Senior Research Engineer for its US R&D Laboratory to research and develop AI/ML-based image processing, computational photography, and CV algorithms for next-gen imaging products.

The role is hybrid (3 days on-site) in San Jose, CA or Culver City, CA or fully remote after training, with occasional travel to Japan. Strong research background and publication history preferred.